Glucagon-Like Peptide-1 Receptor Agonists and Risk of Parkinson's Disease in Patients with Type 2 Diabetes: A Population-Based Cohort Study.

BACKGROUND: Previous studies have suggested that glucagon-like peptide-1 receptor agonists (GLP-1RAs) may have a disease-modifying effect in the development of Parkinson's disease (PD), but population studies yielded inconsistent results. OBJECTIVE: The aim was to compare the risk of PD associated with GLP-1RAs compared to dipeptidyl peptidase 4 inhibitors (DPP4i) among older adults with type 2 diabetes (T2D). METHODS: Using U.S. Medicare administrative data from 2016 to 2020, we conducted a population-based cohort study comparing the new use of GLP-1RA with the new use of DPP4i among adults aged ≥66 years with T2D. The primary endpoint was a new diagnosis of PD. A stabilized inverse probability of treatment weighting (sIPTW)-adjusted Cox proportional hazards regression model was employed to estimate the hazard ratio (HR) and 95% confidence intervals (CI) for PD between GLP-1RA and DPP4i users. RESULTS: This study included 89,074 Medicare beneficiaries who initiated either GLP-1RA (n = 30,091) or DPP4i (n = 58,983). The crude incidence rate of PD was lower among GLP-1RA users than DPP4i users (2.85 vs. 3.92 patients per 1000 person-years). An sIPTW-adjusted Cox model showed that GLP-1RA users were associated with a 23% lower risk of PD than DPP4i users (HR, 0.77; 95% CI, 0.63-0.95). Our findings were largely consistent across different subgroup analyses such as sex, race, and molecular structure of GLP-1RA. CONCLUSION: Among Medicare beneficiaries with T2D, the new use of GLP-1RAs was significantly associated with a decreased risk of PD compared to the new use of DPP4i. © 2024 International Parkinson and Movement Disorder Society.

Evolution of digital twins in precision health applications: a scoping review study.

An increasing amount of research is incorporating the concept of Digital twin (DT) in biomedical and health care applications. This scoping review aims to summarize existing research and identify gaps in the development and use of DTs in the health care domain. The focus of this study lies on summarizing: the different types of DTs, the techniques employed in DT development, the DT applications in health care, and the data resources used for creating DTs. We identified fifty studies, which mainly focused on creating organ- (n=15) and patient-specific twins (n=30). The research predominantly centers on cardiology, endocrinology, orthopedics, and infectious diseases. Only a few studies used real-world datasets for developing their DTs. However, there remain unresolved questions and promising directions that require further exploration. This review provides valuable reference material and insights for researchers on DTs in health care and highlights gaps and unmet needs in this field.

End-of-Life Healthcare Utilization in Lewy Body Dementia.

Background: Lewy body dementia (LBD) is the second most common neurodegenerative dementia in the US, presenting unique end-of-life challenges. Objective: This study examined healthcare utilization and care continuity in the last year of life in LBD. Methods: Medicare claims for enrollees with LBD, continuously enrolled in the year preceding death, were examined from 2011-2018. We assessed hospital stays, emergency department (ED) visits, intensive care unit (ICU) admissions, life-extending procedures, medications, and care continuity. Results: We identified 45,762 LBD decedents, predominantly female (51.8%), White (85.9%), with average age of 84.1 years (SD 7.5). There was a median of 2 ED visits (IQR 1-5) and 1 inpatient stay (IQR 0-2). Higher age was inversely associated with ICU stays (Odds Ratio [OR] 0.96; 95% Confidence Interval [CI] 0.96-0.97) and life-extending procedures (OR 0.96; 95% CI 0.95-0.96). Black and Hispanic patients experienced higher rates of ED visits, inpatient hospitalizations, ICU admissions, life-extending procedures, and in-hospital deaths relative to White patients. On average, 15 (7.5) medications were prescribed in the last year. Enhanced care continuity correlated with reduced hospital (OR 0.72; 95% CI 0.70-0.74) and ED visits (OR 0.71; 95% CI 0.69-0.87) and fewer life-extending procedures (OR 0.71; 95% CI 0.64-0.79). Conclusions: This study underscored the complex healthcare needs of people with LBD during their final year, which was influenced by age and race. Care continuity may reduce hospital and ED visits and life-extending procedures.

COVID-19 Diagnosis, Oral Anticoagulation, and Stroke Risk in Patients with Atrial Fibrillation.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has been associated with an increased risk of stroke. It remains unclear whether the risk of stroke associated with a diagnosis of COVID-19 differed with oral anticoagulation (OAC) use. The aim of this study was to evaluate the association between COVID-19 infection, OAC use, and stroke in patients with atrial fibrillation (AF). METHODS: A retrospective cohort study was conducted in individuals with established AF using data from Optum's deidentified Clinformatics® Data Mart Database. Cox proportional hazard models with time-dependent variables were employed to assess the association between possession of OAC, COVID-19 diagnosis in both inpatient and outpatient setting, and time to ischemic stroke. RESULTS: A total of 561,758 individuals aged 77 ± 10 were included in the study, with a mean follow up time of 1.3 years. OAC use was associated with a reduced stroke risk [hazard ratio (HR) 0.85, 95% confidence interval (CI) 0.82-0.88]. COVID-19 infection was associated with an increased risk of stroke (HR 2.11, 95% CI 1.87-2.38); this increased risk was particularly pronounced for patients diagnosed with an inpatient diagnosis of COVID-19 (HR 3.95, 95% CI 3.33-4.68). There was no significant interaction between OAC use and COVID-19 diagnosis (p value = 0.96). As a result, the relative increase in stroke risk associated with COVID-19 did not differ between patients on OAC (HR 2.12; 95% CI 1.71-2.62) and those not on OAC (HR 2.11; 95% CI 1.83-2.43). CONCLUSION: In a nationwide sample of patients with established AF, we found the relative increase in stroke risk associated with COVID-19 was independent of OAC use.

Trajectories of Sacubitril/Valsartan Adherence Among Medicare Beneficiaries With Heart Failure.

Background: Sacubitril/valsartan, an angiotensin receptor/neprilysin inhibitor (ARNi), improves heart failure (HF) outcomes, yet real-world adherence patterns are not well understood. Objectives: The purpose of this study was to analyze longitudinal patterns of adherence to ARNis in patients with HF and to identify factors associated with adherence patterns. Methods: Using Medicare beneficiaries from 2015 to 2018, we included patients diagnosed with HF who initiated an ARNi. A group-based trajectory model was constructed to identify adherence patterns during follow-up. We used multivariable logistic regression to investigate factors associated with membership in each adherence trajectory group. Results: Among 9,475 eligible beneficiaries (age 77 ± 7 years, 34% female), we identified 5 distinct ARNi adherence trajectories, characterized as: immediate discontinuers, who discontinued treatment within the first 3 months (12%); early discontinuers, who discontinued treatment in months 4 to 7 (10%); late discontinuers, who discontinued treatment in months 7 to 10 (12%); intermittently adherent patients (12%); and consistently adherent patients (54%). The first 4 groups were collectively categorized as nonconsistent adherents. Living in a socioeconomically disadvantaged area, ie, a county with the top 20% of Area Deprivation Index (adjusted OR [aOR]: 1.12 [95% CI: 1.00-1.24]) and Black race (aOR: 1.36, [95% CI: 1.18-1.56]) were associated with a higher likelihood of being nonconsistently adherent. Receiving prescriptions from a cardiologist (aOR: 0.64 [95% CI: 0.57-0.73]) was associated with a lower likelihood of suboptimal ARNi adherence. Conclusions: Half of ARNi users were not consistently adherent to the drug in the first year after treatment initiation. There exist significant racial and socioeconomic inequities in longitudinal adherence to ARNi.

Heterogeneous treatment effects of sodium-glucose cotransporter 2 inhibitors on risk of dementia in people with type 2 diabetes: A population-based cohort study.

INTRODUCTION: Sodium-glucose cotransporter 2 (SGLT2) inhibitors exhibit potential benefits in reducing dementia risk, yet the optimal beneficiary subgroups remain uncertain. METHODS: Individuals with type 2 diabetes (T2D) initiating either SGLT2 inhibitor or sulfonylurea were identified from OneFlorida+ Clinical Research Network (2016-2022). A doubly robust learning was deployed to estimate risk difference (RD) and 95% confidence interval (CI) of all-cause dementia. RESULTS: Among 35,458 individuals with T2D, 1.8% in the SGLT2 inhibitor group and 4.7% in the sulfonylurea group developed all-cause dementia over a 3.2-year follow-up, yielding a lower risk for SGLT2 inhibitors (RD, -2.5%; 95% CI, -3.0% to -2.1%). Hispanic ethnicity and chronic kidney disease were identified as the two important variables to define four subgroups in which RD ranged from -4.3% (-5.5 to -3.2) to -0.9% (-1.9 to 0.2). DISCUSSION: Compared to sulfonylureas, SGLT2 inhibitors were associated with a reduced risk of all-cause dementia, but the association varied among different subgroups. HIGHLIGHTS: New users of sodium-glucose cotransporter 2 (SGLT2) inhibitors were significantly associated with a lower risk of all-cause dementia as compared to those of sulfonylureas. The association varied among different subgroups defined by Hispanic ethnicity and chronic kidney disease. A significantly lower risk of Alzheimer's disease and vascular dementia was observed among new users of SGLT2 inhibitors compared to those of sulfonylureas.

Glucagon-Like Peptide-1 Receptor Agonists and Risk for Suicidal Ideation and Behaviors in U.S. Older Adults With Type 2 Diabetes : A Target Trial Emulation Study.

BACKGROUND: A major concern has recently emerged about a potential link between glucagon-like peptide-1 receptor agonists (GLP-1 RAs) and increased risk for suicidal ideation and behaviors based on International Classification of Diseases codes. OBJECTIVE: To investigate the association between GLP-1 RAs, compared with sodium-glucose cotransporter-2 inhibitors (SGLT2is) or dipeptidyl peptidase-4 inhibitors (DPP4is), and risk for suicidal ideation and behaviors in older adults with type 2 diabetes (T2D). DESIGN: Two target trial emulation studies comparing propensity score (PS)-matched cohorts for GLP-1 RAs versus SGLT2is and GLP-1 RAs versus DPP4is. SETTING: U.S. national Medicare administrative data from January 2017 to December 2020. PATIENTS: Older adults (≥66 years) with T2D; no record of suicidal ideation or behaviors; and a first prescription for a GLP-1 RA, SGLT2i, or DPP4i. MEASUREMENTS: The primary end point was a composite of suicidal ideation and behaviors. New GLP-1 RA users were matched 1:1 on PS to new users of an SGLT2i or DPP4i in each pairwise comparison. A Cox proportional hazards regression was used to estimate the hazard ratio (HR) and 95% CIs within matched groups. RESULTS: This study included 21 807 pairs of patients treated with a GLP-1 RA versus an SGLT2i and 21 402 pairs of patients treated with a GLP-1 RA versus a DPP4i. The HR of suicidal ideation and behaviors associated with GLP-1 RAs relative to SGLT2is was 1.07 (95% CI, 0.80 to 1.45; rate difference, 0.16 [CI, -0.53 to 0.86] per 1000 person-years); the HR relative to DPP4is was 0.94 (CI, 0.71 to 1.24; rate difference, -0.18 [CI, -0.92 to 0.57] per 1000 person-years). LIMITATIONS: Low event rate; imprecise estimates; unmeasured confounders, such as body mass index; and potential misclassification of outcomes. CONCLUSION: Among Medicare beneficiaries with T2D, this study found no clear increased risk for suicidal ideation and behaviors with GLP-1 RAs, although estimates were imprecise and a modest adverse risk could not be ruled out. PRIMARY FUNDING SOURCE: American Foundation for Pharmaceutical Education, Pharmaceutical Research and Manufacturers of America Foundation, National Institute on Aging, and National Institute of Diabetes and Digestive and Kidney Diseases.

Develop and validate a computable phenotype for the identification of Alzheimer's disease patients using electronic health record data.

INTRODUCTION: Alzheimer's disease (AD) is often misclassified in electronic health records (EHRs) when relying solely on diagnosis codes. This study aimed to develop a more accurate, computable phenotype (CP) for identifying AD patients using structured and unstructured EHR data. METHODS: We used EHRs from the University of Florida Health (UFHealth) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UTHealth) and the University of Minnesota (UMN). RESULTS: Our best-performing CP was "patient has at least 2 AD diagnoses and AD-related keywords in AD encounters," with an F1-score of 0.817 at UF, 0.961 at UTHealth, and 0.623 at UMN, respectively. DISCUSSION: We developed and validated rule-based CPs for AD identification with good performance, which will be crucial for studies that aim to use real-world data like EHRs. Highlights: Developed a computable phenotype (CP) to identify Alzheimer's disease (AD) patients using EHR data.Utilized both structured and unstructured EHR data to enhance CP accuracy.Achieved a high F1-score of 0.817 at UFHealth, and 0.961 and 0.623 at UTHealth and UMN.Validated the CP across different demographics, ensuring robustness and fairness.

Association between low cognitive performance and diabetes-related health indicators across racial and ethnic groups in adults with diabetes.

AIM: To examine the associations between low cognitive performance (LCP) and diabetes-related health indicators (including body mass index [BMI], HbA1c, systolic blood pressure [SBP], low-density lipoprotein [LDL] and self-reported poor physical health) and whether these associations vary across racial/ethnic subgroups. METHODS: We identified adults aged 60 years or older with self-reported diabetes from the 2011-2014 National Health and Nutrition Examination Survey. Individuals with cognitive test scores in the lowest quartile were defined as having LCP. We used regression models to measure the associations of LCP with diabetes-related biometrics (BMI, HbA1c, SBP and LDL); and self-reported poor physical health. Moreover, we explored potential variations in these associations across racial/ethnic subgroups. RESULTS: Of 873 (261 with LCP) adults with diabetes, LCP was associated with higher HbA1c, SBP and LDL (adjusted difference: 0.41%, 5.01 mmHg and 5.08 mg/dL, respectively; P < .05), and greater odds of reporting poor physical health (adjusted odds ratio: 1.59, P < .05). The association between LCP and HbA1c was consistent across racial/ethnic groups, and notably pronounced in Hispanic and Other. BMI worsened with LCP, except for non-Hispanic Black. Excluding the Other group, elevated SBP was observed in people with LCP, with Hispanic showing the most significant association. LDL levels were elevated with LCP for Hispanic and Other. Physical health worsened with LCP for both non-Hispanic Black and Hispanic. CONCLUSIONS: We quantified the association between LCP and diabetes-related health indicators. These associations were more pronounced in Hispanic and Other racial/ethnic groups.

Sodium-glucose cotransporter-2 inhibitors and incidence of atrial fibrillation in older adults with type 2 diabetes: a retrospective cohort analysis.

Objectives: To investigate the risk of atrial fibrillation (AF) with sodium-glucose cotransporter-2 inhibitors (SGLT2is) compared to dipeptidyl peptidase-4 inhibitor (DPP4i) use in older US adults and across diverse subgroups. Methods: We conducted a retrospective cohort analysis using claims data from 15% random samples of Medicare fee-for-service beneficiaries. Patients were adults with type 2 diabetes (T2D), no preexisting AF, and were newly initiated on SGLT2i or DPP4i. The outcome was the first incident AF. Inverse probability treatment weighting (IPTW) was used to balance the baseline covariates between the treatment groups including sociodemographics, comorbidities, and co-medications. Cox regression models were used to assess the effect of SGLT2i compared to DPP4i on incident AF. Results: Of the 97,436 eligible individuals (mean age 71.2 ± 9.8 years, 54.6% women), 1.01% (n = 983) had incident AF over a median follow-up of 361 days. The adjusted incidence rate was 8.39 (95% CI: 6.67-9.99) and 11.70 (95% CI: 10.9-12.55) per 1,000 person-years in the SGLT2i and DPP4i groups, respectively. SGLT2is were associated with a significantly lower risk of incident AF (HR 0.73; 95% CI, 0.57 to 0.91; p = 0.01) than DPP4is. The risk reduction of incident AF was significant in non-Hispanic White individuals and subgroups with existing atherosclerotic cardiovascular diseases and chronic kidney disease. Conclusion: Compared to the use of DPP4i, that of SGLT2i was associated with a lower risk of AF in patients with T2D. Our findings contribute to the real-world evidence regarding the effectiveness of SGLT2i in preventing AF and support a tailored therapeutic approach to optimize treatment selection based on individual characteristics.

Comparative Genitourinary Safety of In-class Sodium-Glucose Cotransporter-2 Inhibitors among Patients with Heart Failure with Preserved Ejection Fraction: A Cohort Study.

PURPOSE: The American Heart Association recommended sodium-glucose cotransporter-2 inhibitors (SGLT2i) for the management of heart failure with preserved ejection fraction (HFpEF). However, little is known about their real-world in-class comparative safety in patients with HFpEF. We aimed to assess the comparative safety of SGLT2i in the risk of urinary tract infection (UTI) or genital infection separately or as a composite outcome among patients with HFpEF. METHODS: This cohort study using MarketScan® Commercial and Medicare supplemental databases (2012-2020) included patients aged ≥ 18 years with a diagnosis of HFpEF who initiated SGLT2i therapy. Three pairwise comparison groups were established: cohort 1, dapagliflozin versus canagliflozin; cohort 2, empagliflozin versus canagliflozin; and cohort 3, dapagliflozin versus empagliflozin. After stabilized inverse probability treatment weighting, Cox proportional hazards regression was used to compare the risk of UTI or genital infection separately or as a composite outcome in each cohort. RESULTS: The risk of the composite outcome did not significantly differ between canagliflozin and dapagliflozin (adjusted hazard ratio [aHR] 0.64; 95% confidence interval [CI] 0.36-1.14) or between empagliflozin and canagliflozin (aHR 1.25; 95% CI 0.77-2.05). Similarly, there was no evidence of difference between dapagliflozin and empagliflozin in this risk (aHR 0.76; 95% CI 0.48-1.21). The results of analyses separately assessing UTI or genital infection were similar. CONCLUSIONS: There was no significant difference in the risk of UTI or genital infection among patients with HFpEF who initiated canagliflozin, dapagliflozin, or empagliflozin.

Sodium-glucose cotransporter-2 inhibitors (SGLT2i) are used for the management of heart failure with preserved ejection fraction (HFpEF). It is important to assess their comparative risk of urinary tract infection (UTI) or genital infection among patients with HFpEF. We compared patients with HFpEF using SGLT2i in three pairwise groups: cohort 1, dapagliflozin versus canagliflozin; cohort 2, empagliflozin versus canagliflozin; and cohort 3, dapagliflozin versus empagliflozin. We found that there was no significant difference in the risk of genitourinary infections including UTI or genital infections among dapagliflozin, empagliflozin, and canagliflozin.

Racial and Ethnic Inequities in Spatial Access to Pharmacies: A Geographic Information System Analysis.

BACKGROUND: Pharmacy accessibility is crucial for equity in healthcare access because community pharmacists may reach individuals who do not have access to other healthcare providers. OBJECTIVE: To determine whether spatial access to pharmacies differs among racial/ethnic groups across the rural-urban continuum. METHODS: We obtained a 30% random sample of the Research Triangle Institute (RTI) synthetic population, sampled at the census block level. For each individual, we defined optimal pharmacy access as having a driving distance ≤2 miles to the closest pharmacy in urban counties, ≤5 miles in suburban counties, and ≤10 miles in rural counties. We used a logistic regression model to measure the association between race/ethnicity and pharmacy access, while controlling for racial/ethnic composition of the census tract, Area Deprivation Index, income, age, gender, and US region. The model included an interaction between race/ethnicity and urbanicity to evaluate whether racial/ethnic inequities differed across the rural-urban continuum. RESULTS: The sample included 90,749,446 individuals of whom 80.6% had optimal pharmacy access. Racial/ethnic inequities in pharmacy access differed across the rural-urban continuum (p-value for interaction= <0.0001). In rural areas, Black (OR 0.87; 95%CI 0.86-0.87), Hispanic (OR 0.80; 95%CI 0.79-0.80), and Indigenous (OR 0.47; 95%CI 0.47-0.48) individuals had lower odds of optimal pharmacy access, compared to White individuals. Hispanic (OR 0.96; 95%CI 0.96-0.97) and Indigenous individuals (OR 0.75; 95%CI 0.75-0.76) had lower odds of optimal pharmacy access compared to White individuals in suburban areas. In Western states, Asian had lower odds of optimal pharmacy access in suburban (OR 0.88; 95%CI 0.86-0.90) and rural areas (OR 0.91; 95%CI 0.87-0.95) compared to White Individuals. CONCLUSIONS: Racial/ethnic inequities in spatial access to community pharmacies vary between urban and rural communities. Underrepresented racial/ethnic groups have significantly lower pharmacy access in rural and some suburban areas, but not in urban areas.

COVID-19 pandemic and trends in clinical outcomes and medication use for patients with established atrial fibrillation: A nationwide analysis of claims data.

Study objective: The COVID-19 pandemic disrupted multiple aspects of the health care system, including the diagnosis and control of chronic conditions. This study aimed to quantify pandemic-related changes in the rates of clinical events among patients with atrial fibrillation (AF). Design/setting/participants: In this retrospective cohort study, we identified individuals with established AF at any time before 2019 using de-identified Optum's Clinformatics® Data Mart, and followed them from 3/18/2019 to death, or disenrollment, or the end of the study (09/30/2021). Main outcome: Rates of clinical event, including all-cause hospitalization, ischemic stroke, and bleeding. We constructed interrupted time series to test changes in outcomes after the onset of the COVID-19 pandemic (3/11/2020, date of pandemic declaration). We then identified the first month after the start of the pandemic in which outcomes returned to pre-pandemic levels. Results: A total of 561,758 patients, with a mean age of 77 ± 9.9 years, were included in the study. The monthly incidence rate of all-cause hospitalization decreased from 2.8 % in the period immediately before the pandemic declaration to 1.7 % in the period immediately after, with p-value for level change<0.001. The rate of new ischemic stroke diagnoses decreased from 0.28 % in the period immediately before pandemic declaration to 0.20 % in the period immediately after, and the rate of major bleeding diagnoses from 0.81 % to 0.59 %, both p-values for level change<0.01. The incidence rate of ischemic stroke and bleeding events returned to pre-pandemic levels in October and November 2020, respectively. Conclusions: The COVID-19 pandemic was associated with a decrease in health care visits for ischemic stroke and bleeding in a nationwide cohort of patients with established AF.

Racial/Ethnic Disparities in Use of Angiotensin II Receptor Type 2/4 Stimulatory Vs. Inhibitory Antihypertensive Among Hypertensive Adults in the USA.

OBJECTIVES: Studies showed angiotensin II type 2 receptor/angiotensin II type 4 receptor (AT2R/AT4R) stimulatory antihypertensive was associated with a lower risk of dementia and cognitive impairment compared to the inhibitory one. This study aimed to identify the racial and ethnic differences in using these agents among the USA adults with hypertension. METHODS: A cross-sectional study was conducted using data from the Medical Expenditure Panel Survey (MEPS, 2016-2019). Individuals with a diagnosis of hypertension or self-reported hypertension and without dementia or Alzheimer's disease diagnosis were included in the analysis. We applied two multivariable logistic regressions to compare racial/ethnic differences in AT2R/AT4R stimulatory antihypertensive use and AT2R/AT4R inhibitory antihypertensive use, adjusting for covariates. RESULTS: Twenty-four thousand five hundred eighty-one individuals with hypertension and without dementia or Alzheimer's disease were identified. Among non-Hispanic Whites, 72.39% were using AT2R/AT4R inhibitory antihypertensive agents, vs. 66.97% using AT2R/AT4R stimulatory antihypertensive agents. In contrast, both non-Hispanic Black and Asian Americans were using more AT2R/AT4R stimulatory agents than inhibitory ones (16.40% vs. 12.16% and 4.79% vs. 3.43%, respectively). Compared to non-Hispanic White, non-Hispanic Black (OR 1.980, 95% CI 1.839-2.132) and non-Hispanic Asian Americans (OR 1.545, 95% CI 1.356-1.761) were significantly associated with higher odds of prescribing AT2R/AT4R stimulatory agents, while Hispanics (OR 0.744, 95% CI 0.685-0.808) were associated with lower odds of prescribing AT2R/AT4R inhibitory agents compared to non-Hispanic Whites. CONCLUSIONS: The results showed that the high-dementia risk populations like non-Hispanic Black and Asian American races are proportionally prescribed with higher use of low-dementia risk antihypertensive agents, compared to non-Hispanic Whites.

Comparative effectiveness of sacubitril/valsartan versus angiotensin receptor blockers in patients with heart failure with preserved ejection fraction: A real-world study.

PURPOSE: Sacubitril/valsartan (SAC/VAL) or angiotensin receptor blockers (ARBs) are recommended therapy for heart failure with preserved ejection fraction (HFpEF), but little is known about their real-world comparative effectiveness among patients with HFpEF. The objective of this study was to determine the comparative effectiveness of SAC/VAL vs ARBs in preventing HF-related hospitalization or all-cause hospitalization among patients with HFpEF. METHODS: We conducted a cohort study using IBM MarketScan commercial and Medicare supplemental databases to identify patients aged 18 years or older with a diagnosis of HFpEF and initiation of SAC/VAL (2015-2020) or ARB (2009-2014) therapy. The index date was the date of the first SAC/VAL or ARB prescription fill. After propensity score (PS) matching with a ratio of 1 up to 3, Cox proportional hazards regression was used with robust variance estimators to compare the risks of HF-related hospitalization and all-cause hospitalization between the 2 therapies. Several subgroup and sensitivity analyses were conducted to check the robustness of the main analysis. RESULTS: After PS matching, 2,520 patients (846 receiving SAC/VAL and 1,674 receiving an ARB) were included in the final analyses. After controlling for covariates, there was no difference in the risk of HF-related hospitalization between SAC/VAL and ARB recipients (adjusted hazard ratio [aHR], 1.33; 95% confidence interval [CI], 0.99-1.77). There was also no difference in the risk of all-cause hospitalization between SAC/VAL and ARB recipients (aHR, 1.06; 95% CI, 0.91-1.24). CONCLUSION: Among individuals with private or Medicare Advantage insurance plans, there was no significant difference in the risk of HF-related hospitalization or all-cause hospitalization between adults with HFpEF who received SAC/VAL and those who received ARB therapy.

A scoping review of fair machine learning techniques when using real-world data.

OBJECTIVE: The integration of artificial intelligence (AI) and machine learning (ML) in health care to aid clinical decisions is widespread. However, as AI and ML take important roles in health care, there are concerns about AI and ML associated fairness and bias. That is, an AI tool may have a disparate impact, with its benefits and drawbacks unevenly distributed across societal strata and subpopulations, potentially exacerbating existing health inequities. Thus, the objectives of this scoping review were to summarize existing literature and identify gaps in the topic of tackling algorithmic bias and optimizing fairness in AI/ML models using real-world data (RWD) in health care domains. METHODS: We conducted a thorough review of techniques for assessing and optimizing AI/ML model fairness in health care when using RWD in health care domains. The focus lies on appraising different quantification metrics for accessing fairness, publicly accessible datasets for ML fairness research, and bias mitigation approaches. RESULTS: We identified 11 papers that are focused on optimizing model fairness in health care applications. The current research on mitigating bias issues in RWD is limited, both in terms of disease variety and health care applications, as well as the accessibility of public datasets for ML fairness research. Existing studies often indicate positive outcomes when using pre-processing techniques to address algorithmic bias. There remain unresolved questions within the field that require further research, which includes pinpointing the root causes of bias in ML models, broadening fairness research in AI/ML with the use of RWD and exploring its implications in healthcare settings, and evaluating and addressing bias in multi-modal data. CONCLUSION: This paper provides useful reference material and insights to researchers regarding AI/ML fairness in real-world health care data and reveals the gaps in the field. Fair AI/ML in health care is a burgeoning field that requires a heightened research focus to cover diverse applications and different types of RWD.

Develop and Validate a Computable Phenotype for the Identification of Alzheimer's Disease Patients Using Electronic Health Record Data.

INTRODUCTION: Alzheimer's Disease (AD) are often misclassified in electronic health records (EHRs) when relying solely on diagnostic codes. This study aims to develop a more accurate, computable phenotype (CP) for identifying AD patients by using both structured and unstructured EHR data. METHODS: We used EHRs from the University of Florida Health (UF Health) system and created rule-based CPs iteratively through manual chart reviews. The CPs were then validated using data from the University of Texas Health Science Center at Houston (UT Health) and the University of Minnesota (UMN). RESULTS: Our best-performing CP is " patient has at least 2 AD diagnoses and AD-related keywords " with an F1-score of 0.817 at UF, and 0.961 and 0.623 at UT Health and UMN, respectively. DISCUSSION: We developed and validated rule-based CPs for AD identification with good performance, crucial for studies that aim to use real-world data like EHRs.

Geographic variation and racial disparities in adoption of newer glucose-lowering drugs with cardiovascular benefits among US Medicare beneficiaries with type 2 diabetes.

BACKGROUND: Prior studies have shown disparities in the uptake of cardioprotective newer glucose-lowering drugs (GLDs), including sodium-glucose cotranwsporter-2 inhibitors (SGLT2i) and glucagon-like peptide-1 receptor agonists (GLP1a). This study aimed to characterize geographic variation in the initiation of newer GLDs and the geographic variation in the disparities in initiating these medications. METHODS: Using 2017-2018 claims data from a 15% random nationwide sample of Medicare Part D beneficiaries, we identified individuals diagnosed with type 2 diabetes (T2D), who had ≥1 GLD prescriptions, and did not use SGLT2i or GLP1a in the year prior to the index date,1/1/2018. Patients were followed up for a year. The cohort was spatiotemporally linked to Dartmouth hospital-referral regions (HRRs), with each patient assigned to 1 of 306 HRRs. We performed multivariable Poisson regression to estimate adjusted initiation rates, and multivariable logistic regression to assess racial disparities in each HRR. RESULTS: Among 795,469 individuals with T2D included in the analyses, the mean (SD) age was 73 (10) y, 53.3% were women, 12.2% were non-Hispanic Black, and 7.2% initiated a newer GLD in the follow-up year. In the adjusted model including clinical factors, compared to non-Hispanic White patients, non-Hispanic Black (initiation rate ratio, IRR [95% CI]: 0.66 [0.64-0.68]), American Indian/Alaska Native (0.74 [0.66-0.82]), Hispanic (0.85 [0.82-0.87]), and Asian/Pacific islander (0.94 [0.89-0.98]) patients were less likely to initiate newer GLDs. Significant geographic variation was observed across HRRs, with an initiation rate spanning 2.7%-13.6%. CONCLUSIONS: This study uncovered substantial geographic variation and the racial disparities in initiating newer GLDs.